A data transmission optimization method and optimization system for a multi-stage liquid cooling platform

Abstract

This application discloses a data transmission optimization method and system for a multi-level liquid cooling platform, belonging to the field of transmission optimization technology. The method includes: receiving transmission network information during transmission; extracting node information and transmission link information; dynamically assigning values ​​to the extracted node information and transmission link information; calculating the influence factor of each node on the overall network state and ranking the nodes according to the magnitude of the influence factor; selecting a certain number of nodes based on the data transmission requirements of the multi-level liquid cooling platform, and selecting the nodes to be used based on the ranking results. In the implementation of this application's technical solution, by dividing the wireless transmission process into nodes and transmission links on the nodes, assigning values ​​to the nodes and transmission links respectively, evaluating the network state, ranking the nodes according to their influence on the network state, and selecting a corresponding number of nodes to participate in transmission according to load requirements, the data transmission efficiency is improved.

Description

Technical Field

[0001] The present application relates to the field of transmission optimization technology, and specifically to a data transmission optimization method and optimization system for a multi-stage liquid cooling platform. Background Art

[0002] A liquid cooling platform refers to a system for cooling electronic equipment. It transfers heat from a heat source to a radiator or other cooling device through a liquid medium. Compared with traditional air cooling systems, liquid cooling platforms have higher heat conduction efficiency and can more effectively handle the heat generated by high-power electronic equipment.

[0003] Traditional liquid cooling platforms are usually single-stage liquid cooling modes, which can be used in scenarios with low heat dissipation requirements. This single-stage liquid cooling platform has the advantages of low cost and easy maintenance, and is widely used in the field of equipment heat dissipation. In recent years, with the improvement of the performance of electronic equipment, its heat dissipation requirements have also increased. Traditional single-stage liquid cooling platforms cannot meet the needs, and multi-stage liquid cooling platforms have come into being. Multi-stage liquid cooling platforms can perform heat exchange in multiple stages and can flexibly adjust cooling strategies according to the needs of different components. Therefore, in large electronic equipment, the use of multi-stage liquid cooling platforms can achieve better heat dissipation effects and significantly improve the operating stability of the equipment.

[0004] During the use of the multi-stage liquid cooling platform, it is necessary to continuously monitor various data, such as temperature data of each part, flow rate in the pipeline, pressure data, etc. These data need to be transmitted to the processing center in time for analysis and processing, so as to adjust the multi-stage liquid cooling platform step by step. In addition, due to the limitations of equipment layout, wireless transmission is usually required for data transmission. However, there will be transmission problems such as data delay and data loss during wireless transmission, which will affect the analysis and processing process, resulting in inconsistency between the analysis results and the actual results, and affecting the normal operation of the multi-stage liquid cooling platform.

[0005] Therefore, it is necessary to provide a data transmission optimization method and optimization system for a multi-stage liquid cooling platform to solve the above problems.

[0006] It should be noted that the above information disclosed in this background technology section is only for understanding the background technology of the present application concept, and therefore, it may contain information that does not constitute the prior art. Summary of the invention

[0007] Based on the above-mentioned problems existing in the prior art, the problem to be solved by the present application is: to provide a data transmission optimization method and optimization system for a multi-stage liquid cooling platform, by dividing the wireless transmission process into an evaluation of nodes and transmission links, and selecting nodes from the sorting results to improve the transmission quality.

[0008] The technical solution adopted by the present application to solve the technical problem is: a data transmission optimization method for a multi-stage liquid cooling platform, the optimization method comprising:

[0009] The server receives the transmission network information during the transmission process, and extracts the node information and the transmission link information from the transmission network information, wherein the node represents the device in the transmission network, and the transmission link refers to the wireless channel for transmitting data formed by at least two nodes;

[0010] The server dynamically assigns values ​​to the extracted node information and transmission link information, and evaluates the current overall network status;

[0011] Calculate the impact factor of each node on the overall network status and sort the nodes according to the size of the impact factor;

[0012] According to the data transmission requirements of the multi-stage liquid cooling platform, a certain number of nodes are selected, and the nodes to be used are selected based on the sorting results;

[0013] Establish a dynamic optimization strategy, dynamically adjust the values ​​in each step, set a fixed update time, and periodically update the node ranking results;

[0014] Dynamically assigning values ​​to the extracted node information and transmission link information further includes:

[0015] A quantization value is set for each transmission link. The quantization value is related to the link attribute and is used to represent the transmission quality of the link. The quantization value is proportional to the transmission quality. The higher the quantization value, the higher the transmission quality of the transmission link. The lower the quantization value, the lower the transmission quality of the transmission link.

[0016] Assign values ​​to the nodes between each transmission link. The assignment method is to score the link according to the quantized value of the transmission link, and then obtain the node assignment through weighted average calculation;

[0017] Dynamically adjust node weights to adapt to changes in network load and link status fluctuations;

[0018] Comprehensively evaluate the network status based on the quantitative values ​​of the transmission links.

[0019] During the implementation of the technical solution of the present application, the wireless transmission process is divided into nodes and transmission links on the nodes, and the nodes and transmission links are assigned values ​​respectively, the network status is evaluated, and then the nodes are sorted according to their impact on the network status. The corresponding number of nodes are selected to participate in the transmission according to the load demand, thereby improving the data transmission efficiency.

[0020] Furthermore, the quantized value is obtained by a weight method, which includes: setting different weights for each link attribute according to the relationship between the link attribute and the transmission quality, and comprehensively calculating the quantized value, wherein the sum of all weights is one, and when the link attribute is inversely proportional to the transmission quality, the inverse of the link attribute is taken into account in the calculation process.

[0021] Furthermore, the node assignment method includes: firstly scoring the link by the quantized value of the transmission link, then standardizing the obtained link score, and then calculating the node assignment according to the number of transmission links connected to the node and the corresponding link score.

[0022] Furthermore, the node assignment is calculated using a weighted average method, where the sum of the link scores of the transmission links connected to each node is divided by the number of transmission links connected to the node to obtain the node assignment.

[0023] Furthermore, a method for comprehensively evaluating the network status is to set a data transmission interval for each transmission link, obtain the data transmission volume corresponding to the quantized value of the transmission link through a linear calculation method, and after the transmission link accesses the node, calculate the data transmission interval of the node according to the number of links, and classify the network status according to the data transmission interval of the node, where the network status classification includes three types: good, medium, and poor, and each state corresponds to a numerical interval.

[0024] Furthermore, the method for calculating the influence factor of the node on the overall network status is: calculate the actual data transmission volume of the node under a single link and use it as the first data, then calculate the actual data transmission volume of the node under multiple links and use it as the second data, then divide the first data by the second data, and the result is the influence factor of the node on the overall network status, and sort the corresponding nodes according to size.

[0025] A data transmission optimization system for a multi-stage liquid cooling platform, comprising:

[0026] A data receiving module is used for the server to receive the transmission network information during the transmission process, and extract the node information and the transmission link information from the transmission network information, wherein the node represents the equipment in the transmission network, and the transmission link refers to the wireless channel for transmitting data formed by at least two nodes;

[0027] The dynamic assignment module is used by the server to dynamically assign values ​​to the extracted node information and transmission link information, and evaluate the current overall network status;

[0028] The impact factor calculation module is used to calculate the impact factor of each node on the overall network status and sort the nodes according to the size of the impact factor;

[0029] The node selection module is used to select a certain number of nodes according to the data transmission requirements of the multi-stage liquid cooling platform, and select the nodes to be used according to the sorting results;

[0030] The dynamic optimization module is used to establish a dynamic optimization strategy, dynamically adjust the values ​​in each step, set a fixed update time, and periodically update the node sorting results.

[0031] The beneficial effects of the present application are: a data transmission optimization method and optimization system for a multi-stage liquid cooling platform provided by the present application divides the wireless transmission process into nodes and transmission links on the nodes, and assigns values ​​to the nodes and transmission links respectively, evaluates the network status, and then sorts the nodes according to their impact on the network status, selects a corresponding number of nodes to participate in the transmission according to load requirements, and improves data transmission efficiency.

[0032] In addition to the above-described purposes, features and advantages, the present application also has other purposes, features and advantages. The present application will be further described in detail with reference to the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The drawings constituting part of the present application are used to provide a further understanding of the present application. The exemplary embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0034] Figure 1 It is a schematic diagram of the overall process of a data transmission optimization method of a multi-stage liquid cooling platform in this application;

[0035] Figure 2 This is a schematic diagram of the module structure of a data transmission optimization system for a multi-stage liquid cooling platform in this application. DETAILED DESCRIPTION

[0036] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0037] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0038] Embodiment 1: Figure 1As shown, the present application provides a data transmission optimization method for a multi-stage liquid cooling platform. The method is applied to the multi-stage liquid cooling platform to optimize the data transmission links involved in the operation of the multi-stage liquid cooling platform, improve the liquid cooling effect of each level, and prevent the heat dissipation effect of the multi-stage liquid cooling platform from decreasing due to problems in the data transmission process. The method is mainly applied to wireless transmission methods and can also be applied to other similar scenarios. The data transmission optimization method includes:

[0039] Step 10: The server receives the transmission network information during the transmission process, and extracts the node information and the transmission link information from the transmission network information, wherein the node represents the device in the transmission network, and the transmission link refers to the wireless channel for transmitting data formed by at least two nodes;

[0040] The operation of the multi-stage liquid cooling platform involves a large amount of data collection and transmission. These data not only include real-time monitoring parameters such as temperature, pressure and flow, but also cover key information such as equipment status, fault diagnosis and energy efficiency analysis. In order to ensure the accuracy and real-time nature of the data, high-precision sensors or high-speed data acquisition cards are usually required. During the data transmission process, wired transmission or wireless transmission can be selected to transmit the data. In this embodiment, wireless transmission is taken as an example.

[0041] After data collection, it is also necessary to process and analyze the data. Therefore, the multi-stage liquid cooling platform is usually equipped with a server, which refers to a hardware unit with functions such as data reception, processing, and analysis. The unit is responsible for coordinating the operation of various subsystems and executing complex control strategies. The server will dynamically adjust the flow, temperature, pressure and other parameters of the coolant based on the collected data through other control algorithms, such as PID control, fuzzy control or neural network control, to achieve regulation of the multi-stage liquid cooling platform.

[0042] During the wireless transmission process, a transmission network is involved. The transmission network consists of multiple nodes and multiple transmission links. The nodes represent devices in the transmission network, such as acquisition equipment, network relay equipment, etc. The transmission link refers to a wireless channel for transmitting data composed of at least two nodes. Combining nodes and transmission links into a transmission network can achieve efficient data transmission. After receiving the transmission network information, the server will extract node information and transmission link information from this information. This information is crucial for subsequent transmission optimization.

[0043] Step 20: The server dynamically assigns values ​​to the extracted node information and transmission link information, and evaluates the current overall network status;

[0044] In the process of wireless transmission, node information and transmission link information are related to the quality and success rate of transmission. Node information represents various devices, and transmission link information represents the transmission channel between various devices. At different times, node information and transmission link information will undergo uncertain changes. Such uncertain changes will affect the evaluation of the transmission process. By dynamically assigning values ​​to the extracted node information and transmission link information, the changes can be quantified, which is convenient for evaluating the network status. Specifically, the dynamic assignment of the extracted node information and transmission link information further includes:

[0045] Step 201: setting a quantization value for each transmission link, where the quantization value is related to the link attribute and is used to represent the transmission quality of the link;

[0046] In a transmission link, there are many link attributes that determine the network status, such as bandwidth, packet loss rate, signal strength, etc., and the quantization value is used to indicate the transmission quality of the link. It should be noted that the quantization value is proportional to the transmission quality. The higher the quantization value, the higher the transmission quality of the link. On the contrary, the lower the quantization value, the lower the transmission quality of the link. When setting the quantization value, it is necessary to comprehensively consider different link attributes and obtain it through the weight method;

[0047] Specifically, according to the relationship between link attributes and transmission quality, different weights are set for each link attribute, and the quantized value is calculated comprehensively. For example, the link attributes include bandwidth, delay, transmission distance, and packet loss rate. According to the relationship between these link attributes and transmission quality, different weight factors are set respectively. The weight factors not only indicate the influence of different link attributes on the quantized value, but also can normalize different link attributes. For example, the weights of bandwidth, delay, transmission distance, and packet loss rate are w1, w2, w3, and w4 respectively. These weight values ​​can be adjusted according to actual conditions, and the sum of all weights is one. The calculation formula of the quantized value can be expressed as: Quantized value = w1*B+w2*1 / D+w3*1 / S+w4*1 / P, where B represents bandwidth, D represents delay, S represents transmission distance, and P represents packet loss rate. This calculation method can ensure that the quantized value reflects the actual transmission situation of the link more accurately. It should be noted that when the link attribute is inversely proportional to the transmission quality, the reciprocal of the link attribute needs to be taken in the calculation process. In order to reflect the actual transmission scenario, all values ​​are positive numbers. After the calculation is completed, the obtained quantized value is the transmission quality of the transmission link.

[0048] Step 202: assigning a value to a node between each transmission link, wherein the assignment method is to score the link according to the quantized value of the transmission link, and then obtain the node assignment by weighted average calculation;

[0049] There are multiple transmission links on each node. After calculating the quantized value of each transmission link, the node can be assigned a value based on the quantized value. This assignment method not only reflects the importance of the node in the overall network, but also reflects its contribution to network performance. Combining the node with the transmission link facilitates subsequent network status evaluation.

[0050] Specifically, the node assignment method includes: firstly, performing link scoring by using the quantized value of the transmission link, wherein the scoring method is to input the quantized value of the transmission link into the linear regression model through a linear regression model, and output the link score, or to optimize the link score by using a machine learning algorithm, which may be specifically referred to in the prior art and will not be described in detail in this embodiment;

[0051] Then, the node assignment calculation is performed. Since each node is connected to multiple transmission links, the node assignment needs to be calculated based on the number of transmission links connected to the node and its corresponding link score. Specifically, the weighted average method is used for calculation. The calculation method of the node assignment is: the sum of the link scores of the transmission links connected to each node is divided by the number of transmission links connected to the node. This takes into account both the link score and the node connection density, making the node assignment more comprehensive.

[0052] Step 203: Dynamically adjust the weight of the node to adapt to changes in network load and link status fluctuations. In this step, an adaptive adjustment mechanism is introduced to fine-tune the node assignment by real-time monitoring of network performance indicators to ensure the accuracy and timeliness of network status evaluation. In addition, in order to improve evaluation efficiency, parallel processing technology is used to perform distributed calculations on large-scale network node data, reduce calculation complexity, and improve overall evaluation efficiency.

[0053] Step 204: Comprehensively evaluate the network status according to the quantized value of the transmission link.

[0054] After obtaining the quantized value of the transmission link and the assignment of the node, it is necessary to comprehensively evaluate the network status based on these parameters. Specifically, the method for comprehensively evaluating the network status is to set a data volume transmission interval for each transmission link. The interval is [0, A], which means that the data volume transmission range of a single transmission link is 0 to A. When the transmission data volume is 0, it means that the link is not transmitting data. When the transmission data volume is A, it means that the data volume transmitted by the link is A, where A is the data transmission volume in bytes. The specific value is obtained by converting the quantized value of the transmission link into data volume, and obtaining the data transmission volume corresponding to the quantized value of the transmission link through a linear calculation method. After the transmission link accesses the node, it is also necessary to calculate the data volume transmission interval of the node according to the number of links, and classify the network status according to the data volume transmission interval of the node. The network status classification includes three types: good, medium, and poor, and each state corresponds to a numerical interval;

[0055] Specifically, when the transmission links are the same, the data volume transmission interval of the node is equal to the sum of the data volume transmission intervals of the transmission links connected to it. For example, when a node is connected to three identical transmission links, the data volume transmission interval of the node is [0, A+A+A]. In addition, the network status needs to be classified according to the actual data transmission volume of the node. In this embodiment, the interval corresponding to the good state is [2A, 3A], the interval corresponding to the medium state is [A, 2A], and the interval corresponding to the poor state is [0, A].

[0056] Step 30: Calculate the impact factor of each node on the overall network status, and sort the nodes according to the size of the impact factor;

[0057] After obtaining the overall network status, it is necessary to further analyze the degree of influence of each node on the network performance, because during data transmission, not all nodes need to be used. Therefore, it is necessary to screen out the most suitable nodes under the current network status. During the screening process, nodes with high influence factors will undertake more important data transmission tasks. Specifically, the calculation method of the influence factor of the node on the overall network status is: calculate the actual data transmission volume of the node under a single link and use it as the first data, then calculate the actual data transmission volume of the node under multiple links and use it as the second data, then divide the first data by the second data, and the result is the influence factor of the node on the overall network status, and sort the corresponding nodes according to the size of the influence factor. Under a single link, the actual data transmission volume of the node is usually fixed, while under multiple links, due to unexpected factors such as loss and selection involved in the transmission process, the actual transmission volume will change. Therefore, the actual data transmission volume of the node under a single link is divided by the actual data transmission volume of the node under multiple links, and the result is used as the influence factor;

[0058] Step 40: Select a certain number of nodes according to the data transmission requirements of the multi-stage liquid cooling platform, and select the nodes to be used according to the sorting results;

[0059] During the use of the multi-stage liquid cooling platform, different load scenarios correspond to different data transmission requirements. Therefore, according to the data transmission requirements of the multi-stage liquid cooling platform, a certain number of nodes are selected, and then selected from the sorting results according to this number. For example, during the operation of the multi-stage liquid cooling platform, fifteen nodes are required for transmission under the current load, then the first fifteen nodes are selected from the sorting results as the selection, and the next node is additionally selected as a redundant node to prevent abnormalities in the first fifteen nodes and replace them in time. This method ensures the high efficiency of data transmission and the stability of the system, and there is no need to put all nodes into use, saving load;

[0060] It should be noted that the selection of the number of nodes is related to the data transmission requirements of the multi-stage liquid cooling platform. Since the data transmission volume is directly proportional to the transmission demand, the linear value method can be used to calculate the number of nodes, obtain the data transmission volume of the multi-stage liquid cooling platform, and obtain a node number based on the transmission volume. The number of nodes is selected by rounding up to prevent the situation where the number of nodes is insufficient due to fluctuations in data transmission volume.

[0061] Step 50: Establish a dynamic optimization strategy, dynamically adjust the values ​​in each step, set a fixed update time, and periodically update the node sorting results.

[0062] After completing the above steps, it is also necessary to establish a dynamic optimization strategy to dynamically adjust the values ​​in each step to adapt to the real-time changes in network status. This strategy will ensure the accuracy and real-time performance of the node sorting results. At the same time, according to the operating status of the multi-stage liquid cooling platform, the dynamic optimization strategy will automatically adjust the number of nodes and selection criteria to maintain efficient operation of the system and reasonable allocation of resources. In addition, the node sorting results can be updated periodically in a timely manner through periodic updates to prevent the impact of network fluctuations on nodes from radiating to the node selection in the transmission process.

[0063] Embodiment 2: Figure 2 As shown, the present application also proposes a data transmission optimization system for a multi-stage liquid cooling platform, the system runs the optimization method in embodiment 1, and the system includes:

[0064] A data receiving module is used for the server to receive the transmission network information during the transmission process, and extract the node information and the transmission link information from the transmission network information, wherein the node represents the equipment in the transmission network, and the transmission link refers to the wireless channel for transmitting data formed by at least two nodes;

[0065] The dynamic assignment module is used by the server to dynamically assign values ​​to the extracted node information and transmission link information, and evaluate the current overall network status;

[0066] The impact factor calculation module is used to calculate the impact factor of each node on the overall network status and sort the nodes according to the size of the impact factor;

[0067] The node selection module is used to select a certain number of nodes according to the data transmission requirements of the multi-stage liquid cooling platform, and select the nodes to be used according to the sorting results;

[0068] The dynamic optimization module is used to establish a dynamic optimization strategy, dynamically adjust the values ​​in each step, set a fixed update time, and periodically update the node sorting results.

[0069] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A data transmission optimization method for a multi-stage liquid cooling platform, characterized in that: The optimization method includes: The server receives the transmission network information during the transmission process, and extracts the node information and the transmission link information from the transmission network information, wherein the node represents the device in the transmission network, and the transmission link refers to the wireless channel for transmitting data formed by at least two nodes; The server dynamically assigns values ​​to the extracted node information and transmission link information, and evaluates the current overall network status; Calculate the influence factor of each node on the overall network state, and sort the nodes according to the size of the influence factor; the calculation method of the influence factor of the node on the overall network state is: calculate the actual data transmission volume of the node under a single link and use it as the first data, then calculate the actual data transmission volume of the node under multiple links and use it as the second data, then divide the first data by the second data, and the result is the influence factor of the node on the overall network state, and sort the corresponding nodes according to the size; According to the data transmission requirements of the multi-stage liquid cooling platform, a certain number of nodes are selected, and the nodes to be used are selected based on the sorting results; Establish a dynamic optimization strategy, dynamically adjust the values ​​in each step, set a fixed update time, and periodically update the node ranking results; Dynamically assigning values ​​to the extracted node information and transmission link information further includes: A quantization value is set for each transmission link. The quantization value is related to the link attribute and is used to represent the transmission quality of the link. The quantization value is proportional to the transmission quality. The higher the quantization value, the higher the transmission quality of the transmission link. The lower the quantization value, the lower the transmission quality of the transmission link. Assign values ​​to the nodes between each transmission link. The assignment method is to score the link according to the quantized value of the transmission link, and then obtain the node assignment through weighted average calculation; Dynamically adjust node weights to adapt to changes in network load and link status fluctuations; Comprehensively evaluate the network status based on the quantitative values ​​of the transmission links.

2. The data transmission optimization method of a multi-stage liquid cooling platform according to claim 1, characterized in that: The quantized value is obtained by using a weight method, which includes: setting different weights for each link attribute according to the relationship between the link attribute and the transmission quality, and comprehensively calculating the quantized value, wherein the sum of all weights is one, and when the link attribute is inversely proportional to the transmission quality, the inverse of the link attribute is taken to participate in the calculation during the calculation process.

3. The data transmission optimization method of a multi-stage liquid cooling platform according to claim 1, characterized in that: The node assignment method includes: firstly scoring the link by the quantized value of the transmission link, then standardizing the obtained link score, and then calculating the node assignment according to the number of transmission links connected to the node and its corresponding link score.

4. The data transmission optimization method of a multi-stage liquid cooling platform according to claim 3, characterized in that: The node assignment is calculated using the weighted average method, which is the sum of the link scores of the transmission links connected to each node, divided by the number of transmission links connected to the node to obtain the node assignment.

5. The data transmission optimization method of a multi-stage liquid cooling platform according to claim 1, characterized in that: The method for comprehensively evaluating the network status is to set a data transmission interval for each transmission link, obtain the data transmission volume corresponding to the quantized value of the transmission link through a linear calculation method, calculate the data transmission interval of the node according to the number of links after the transmission link accesses the node, and classify the network status according to the data transmission interval of the node, where the network status classification includes good, medium, and poor, and each state corresponds to a numerical interval.

6. A data transmission optimization system for a multi-stage liquid cooling platform, characterized in that: include: A data receiving module is used for the server to receive the transmission network information during the transmission process, and extract the node information and the transmission link information from the transmission network information, wherein the node represents the equipment in the transmission network, and the transmission link refers to the wireless channel for transmitting data formed by at least two nodes; The dynamic assignment module is used by the server to dynamically assign values ​​to the extracted node information and transmission link information, and evaluate the current overall network status; Dynamically assigning values ​​to the extracted node information and transmission link information further includes: A quantization value is set for each transmission link. The quantization value is related to the link attribute and is used to represent the transmission quality of the link. The quantization value is proportional to the transmission quality. The higher the quantization value, the higher the transmission quality of the transmission link. The lower the quantization value, the lower the transmission quality of the transmission link. Assign values ​​to the nodes between each transmission link. The assignment method is to score the link according to the quantized value of the transmission link, and then obtain the node assignment through weighted average calculation; Dynamically adjust node weights to adapt to changes in network load and link status fluctuations; Comprehensively evaluate the network status based on the quantified values ​​of the transmission links; The influence factor calculation module is used to calculate the influence factor of each node on the overall network state, and sort the nodes according to the size of the influence factor; the influence factor calculation method of the node on the overall network state is: calculate the actual data transmission volume of the node under a single link and use it as the first data, then calculate the actual data transmission volume of the node under multiple links and use it as the second data, then divide the first data by the second data, and the result is the influence factor of the node on the overall network state, and sort the corresponding nodes according to the size; The node selection module is used to select a certain number of nodes according to the data transmission requirements of the multi-stage liquid cooling platform, and select the nodes to be used according to the sorting results; The dynamic optimization module is used to establish a dynamic optimization strategy, dynamically adjust the values ​​in each step, set a fixed update time, and periodically update the node sorting results.

7. The data transmission optimization system of a multi-stage liquid cooling platform according to claim 6, characterized in that: Used to implement the data transmission optimization method of the multi-stage liquid cooling platform as described in any one of claims 1 to 5.

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